INTERNET-DRAFT Donald E. Eastlake 3rd
Motorola
OBSOLETES: RFC 2777 November 2001
Expires May 2002
Publicly Verifiable NomCom Random Selection
-------- ---------- ------ ------ ---------
<draft-eastlake-rfc2777bis-selection-01.txt>
Status of this Memo
This draft is intended to become an Informational RFC. Distribution
of this document is unlimited. Comments should be sent to the author.
This document is an Internet-Draft and is in full conformance with
all provisions of Section 10 of RFC 2026. Internet-Drafts are
working documents of the Internet Engineering Task Force (IETF), its
areas, and its working groups. Note that other groups may also
distribute working documents as Internet-Drafts.
Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
The list of current Internet-Drafts can be accessed at
http://www.ietf.org/ietf/1id-abstracts.txt
The list of Internet-Draft Shadow Directories can be accessed at
http://www.ietf.org/shadow.html.
Abstract
This document describes a method for making random selections in such
a way that the unbiased nature of the choice is publicly verifiable.
As an example, the selection of the voting members of the IETF
Nominations Committee from the pool of eligible volunteers is used.
Similar techniques would be applicable to other cases.
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Acknowledgements
Matt Crawford made major contributions to this document and comments
by Bernard Aboba, Theodore Ts'o and others have been incorporated.
Table of Contents
Status of this Memo........................................1
Abstract...................................................1
Acknowledgements...........................................2
Table of Contents..........................................2
1. Introduction............................................3
2. General Flow of a Publicly Verifiable Process...........3
2.1 Determination of the Pool..............................3
2.2 Publication of the Algorithm...........................3
2.3 Publication of Selection...............................4
3. Randomness..............................................4
3.1 Sources of Randomness..................................4
3.2 Skew...................................................5
3.3 Entropy Needed.........................................5
4. A Suggested Precise Algorithm...........................6
5. Handling Real World Problems............................7
5.1 Uncertainty as to the Pool.............................7
5.2 Vacancies in NomCom....................................8
5.3 Randomness Ambiguities.................................9
6. Fully Worked Example....................................9
7. Security Considerations................................11
8. Reference Code.........................................12
Appendix A: History of NomCom Member Selection............18
Appendix B: Changes from RFC 2777.........................18
References................................................19
Author's Address..........................................19
File name and Expiration..................................19
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1. Introduction
Under the IETF rules, each year ten people are randomly selected from
among eligible volunteers to be the voting members of the IETF
nominations committee (NomCom). The NomCom nominates members of the
Internet Engineering Steering Group (IESG) and the Internet
Architecture Board (IAB) as described in [RFC 2727]. The number of
eligible volunteers in recent years has varied in the approximate
range of 40 to 100.
It is highly desirable that the random selection of the voting NomCom
be done in an unimpeachable fashion so that no reasonable charges of
bias or favoritism can be brought. This is as much for the protection
of the selection administrator (currently, the appointed non-voting
NomCom chair) from suspicion of bias as it is for the protection of
the IETF.
A method such that public information will enable any person to
verify the randomness of the selection meets this criterion. This
document gives an example of such a method.
2. General Flow of a Publicly Verifiable Process
In general, a selection of NomCom members publicly verifiable as
unbiased or similar selection could follow the three steps given
below.
2.1 Determination of the Pool
First, you need to determine the pool from which the selection is to
be made.
Volunteers are solicited by the selection administrator. Their names
are then passed through the IETF Secretariat to check eligibility.
(Current eligibility criteria relate to IETF meeting attendance,
records of which are maintained by the Secretariat.) The full list
of eligible volunteers should be made public early enough that a
reasonable time can be given to resolve any disputes as to who should
be in the pool, probably a week to ten days.
2.2 Publication of the Algorithm
The exact algorithm to be used, including the public future sources
of randomness, is made public. For example, the members of the final
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list of eligible volunteers are ordered by publicly numbering them,
some public future sources of randomness such as government run
lotteries are specified, and an exact algorithm is specified whereby
eligible volunteers are selected based on a strong hash function [RFC
1750] of these future sources of randomness.
2.3 Publication of Selection
When the pre-specified sources of randomness produce their output,
those values plus a summary of the execution of the algorithm for
selection should be announced so that anyone can verify that the
correct randomness source values were used and the algorithm properly
executed. A cut off time for any complaint that the algorithm was run
with the wrong inputs or not faithfully executed should be specified
to finalize the output and provide a stable NomCom.
3. Randomness
The crux of the unbiased nature of the selection is that it is based
in an exact, predetermined fashion on random information which will
be revealed in the future and thus can not be known to the person
specifying the algorithm. That random information will be used to
control the selection. The random information must be such that it
will be publicly and unambiguously revealed in a timely fashion.
The random sources must not include anything that any reasonable
person would believe to be under the control or influence of the IETF
or its components, such as IETF meeting attendance statistics,
numbers of documents issued, or the like.
3.1 Sources of Randomness
Examples of good information to use are winning lottery numbers for
specified runnings of specified lotteries. Particularly for
government run lotteries, great care is taken to see that they
produce random quantities. Even in the unlikely case one were to
have been rigged, it would almost certainly be in connection with
winning money in the lottery, not in connection with IETF use.
Other possibilities are such things as the daily balance in the US
Treasury on a specified day, the volume of trading on the New York
Stock exchange on a specified day, etc. (However, the reference code
given below will not handle integers that are too large.) Sporting
events can also be used. (Experience has indicated that stock prices
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and/or volumes are a poor source of unambiguous data due to their not
trading on some days, mergers, delistings, splits, multiple markets,
etc.) In all cases, great care must be taken to specify exactly what
quantities are being presumed random and what will be done if their
issuance is cancelled or delayed.
It is important that the last source of randomness, chronologically,
produce a substantial amount of the entropy needed. If most of the
randomness has come from the earlier of the specified sources, and
someone has even limited influence on the final source, they might do
an exhaustive analysis and exert such influence so as to bias the
selection in the direction they wanted. Thus it is best for the last
source to be an especially strong and unbiased source of a large
amount of randomness such as a government run lottery.
It is best not to use too many different sources. Every additional
source increases the probability that one or more sources might be
delayed, cancelled, or just plain screwed up somehow, calling into
play contingency provisions or, worst of all, creating a situation
that was not anticipated. This would either require arbitrary
judgement by the selection administrator, defeating the randomness of
the selection, or a re-run of with a new set of sources, causing much
delay. A good number of sources is three. Ten is probably too many.
3.2 Skew
Some of the sources of randomness produce data which is not uniformly
distributed. This is certainly true of volumes, prices, and horse
race results, for example. However, use of a strong mixing function
[RFC 1750] will extract the available entropy and produce a hash
value whose bits, remainder modulo a small divisor, etc., are
uniformly distributed.
3.3 Entropy Needed
What we are doing is selection N items without replacement from a
population of P items. The number of different ways to do this is as
follows, where "!" represents the factorial function:
P!
-------------
N! * (P - N)!
To do this in a completely random fashion requires as many random
bits as the logarithm base 2 of that quantity. Some sample
calculated approximate number of random bits for the selection of 10
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NomCom members from various pool sizes is given below:
Random Selection of Ten Items From Pool
Pool size 20 25 30 35 40 50 60 75 100
Bits needed 18 22 25 28 30 34 37 40 44
Using an inadequate number of bits means that not all of the possible
selections would be available. For a substantially inadequate amount
of entropy, there could be a correlation between the selection of two
different members of the pool, for example. However, as a practical
matter, for pool sizes likely to be encountered in IETF NomCom
membership selection, 40 bits of entropy should always be adequate.
Even if there is a large pool and theoretically more bits are needed
for complete randomness, 40 bits of entropy will assure that the
probability of selection of each pool member differs from that of
other pool members, the correlation between the selection of any pair
of pool members, etc., differs only insignificantly from that for
completely random selection.
An MD5 [RFC 1321] hash has 128 bits and therefore can produce no more
than that number of bits of entropy. However, this is three times
what is likely to ever be needed for IETF NomCom membership
selection. A stronger hash such as SHA-1 [RFC 3174] can be used if
desired.
4. A Suggested Precise Algorithm
It is important that a precise algorithm be given for mixing the
random sources specified and making the selection based thereon.
Sources suggested above produce either a single positive number
(i.e., NY Stock Exchange volume in thousands of shares) or a small
set of positive numbers (many lotteries provide 6 numbers in the
range of 1 through 40 or the like, a sporting event could produce the
scores of two teams, etc.). A sample precise algorithm is as
follows:
1. For each source producing multiple numeric values, represent each
as a decimal number terminated by a period (or with a period
separating the whole from the fractional part) and without leading
zeroes (except for a single leading zero if the integer part is
zero) or trailing zeroes after the period.
2. Order them from smallest to the largest and concatenate them and
suffix the result with a "/". For each source producing a single
number, simply represent it as above with a suffix "/". (This
sorting is necessary because the same lottery results, for
example, are sometimes reported in the order numbers were drawn
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and sometimes in numeric order.)
3. At this point you have a string for each source, say s1/, s2/, ...
Concatenate these strings in a pre-specified order and represent
each character as its ASCII code producing s1/s2/.../.
You then produce a sequence of random values derived from a strong
mixing of these sources by calculating the MD5 hash [RFC 1321] of
this string prefixed and suffixed with a zero byte for the first
value, the string prefixed and suffixed by a 0x01 byte for the second
value, etc. Treat each of these derived random values as a positive
multiprecision integer. Then totally order the pool of listed
volunteers as follows: If there are P volunteers, select the first by
dividing the first derived random value by P and using the remainder
plus one as the position of the selectee in the published list.
Select the second by dividing the second derived random value by P-1
and using the remainder plus one as the position in the list with the
first selected person eliminated. Etc.
It is recommended that alphanumeric random sources be avoided due to
the greater difficulty in canonicalizing them in an independently
repeatable fashion; however, if any are used, all white space,
punctuation, and special characters should be removed and all letters
set to upper case. This will leave only an unbroken sequence of
letters A-Z and digits 0-9 which can be treated as a canonicalized
number above and suffixed with a "/".
5. Handling Real World Problems
In the real world, problems can arise in following the steps and flow
outlined in Sections 2 through 4 above. Some problems that have
actually arisen are described below with recommendations for handling
them.
5.1 Uncertainty as to the Pool
Every reasonable effort should be made to see that the published pool
from which selection is made is of certain and eligible persons.
However, especially with compressed schedules or perhaps someone
whose claim that they volunteered and are eligible has not been
resolved by the deadline, or a determination that someone is not
eligible which occurs after the publication of the pool, it may be
that there are still uncertainties.
The best way to handle this is to maintain the announced schedule,
INCLUDE in the published pool all those whose eligibility is
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uncertain and to keep the published pool list numbering IMMUTABLE
after its publication. If someone in the pool is later selected by
the algorithm and random input but it has been determined they are
ineligible, they must be skipped and the algorithm used further to
make an additional selection. Thus the uncertainty only effects one
selection and in general no more than a maximum of N selections where
there are N uncertain pool members.
Other courses of action are far worse. Actual insertion or deletion
of entries in the pool after its publication changes the length of
the list and totally scrambles who is selected, possibly changing
every selection. Insertion into the pool raises questions of where to
insert: at the beginning, end, alphabetic order, ... Any such choices
by the selection administrator after the random numbers are known
destroys the public verifiability of fair choice. Even if done before
the random numbers are known, such dinking with the list after its
publication just doesn't smell good. There should be clear fixed
public deadlines and someone who challenges their absence from the
pool after the published deadline should have their challenge
automatically denied for tardiness.
5.2 Vacancies in NomCom
The ordering produced by the algorithm may needs to go used beyond
the exact number to be select to allow for ineligibles, those who
back out when actually contacted and asked to affirm their
willingness to serve and maintain NomCom confidentiality, and those
that can't be contacted.
Yes, it has actually occurred that an eligible volunteer has been
selected and found to be uncontactable, despite repeated good faith
efforts over a period of weeks by email, telephone, and postal mail,
including trying to go through their employer. There really isn't
much choice in such as case other than to treat them as not
consenting and go on to the next person selected. So, it might be a
good idea in early announcements to make it clear that volunteers
need to be contactable during, say, the week after the last random
number is available. (Many enthusiastic volunteers have, in the past,
spontaneously told the selection administrator how to contact them if
they were going to be on vacation, etc.)
Vacancies occurring in the NomCom after it has been established and
is in operation are a little different. It is generally recommended
that the original ordering of the eligible pool be followed and the
next volunteer according to the original algorithm and random inputs
be contacted. Using new announced future random number inputs to
select from the remainder of the pool is not recommended as it may be
impractical due to delays. Asking for a new pool of volunteers would
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be even worse and should be avoided except in the extraordinary case,
unlikely to ever occur, where the eligible pool has been depleted or
is nearly so. If the NomCom is near to finishing its work, it may not
be worth filling a vacancy.
5.3 Randomness Ambiguities
The best good faith efforts have been made to specify precise and
unambiguous sources of randomness. These sources are made public in
advance and there has not been objection to them. However, it has
happened that when the time comes to actually get and use this
randomness, the real world has thrown a curve ball and it isn't quite
clear what data to use. Problems have particularly arisen in
connection with stock prices, volumes, and obscure financial exchange
rates or indices. If volumes that were published in thousands are
published in hundreds, you have a rounding problem. Prices that were
quoted in fractions or decimals can change to the other. If you take
care of every contingency that has come up in the past, you can be
hit with a new one. When this sort of thing happens, it is generally
too late to announce new sources, an action which would raise
suspicions of its own. About the only course of action is to make a
reasonable choice within the ambiguity and depend on confidence in
the good faith of the selection administrator. With care, such cases
should be very rare.
Based on these experiences, it is again recommended that government
run Lottery numbers or the like be used as the random inputs and
stock prices and volumes avoided.
6. Fully Worked Example
Assume the following ordered list of 25 eligible volunteers is
published in advance of selection:
1. John 11. Pollyanna 21. Pride
2. Mary 12. Pendragon 22. Sloth
3. Bashful 13. Pandora 23. Envy
4. Dopey 14. Faith 24. Anger
5. Sleepy 15. Hope 25. Kasczynski
6. Grouchy 16. Charity
7. Doc 17. Lee
8. Sneazy 18. Longsuffering
9. Handsome 19. Chastity
10. Cassandra 20. Smith
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Assume the following (fake example) ordered list of randomness
sources:
1. The Kingdom of Alphaland State Lottery daily number for 1 November
2001 treated as a single four digit integer.
2. Numbers of the winning horses at Hialeia for all races for the
first day on or after 13 October 2001 on which at least two races
are run.
3. The People's Democratic Republic of Betastani State Lottery six
winning numbers (ignoring the seventh "extra" number) for 1
November 2001.
Randomness publicly produced:
Source 1: 9319
Source 2: 2, 5, 12, 8, 10
Source 3: 9, 18, 26, 34, 41, 45
Resulting key string:
9319./2.5.8.10.12./9.18.26.34.41.45./
The table below gives the hex of the MD5 of the above key string
bracketed with a byte whose value is successively 0x00, 0x01, 0x02,
through 0x18 (24 decimal). The divisor for the number size of the
remaining pool at each stage is given and the index of the selectee
as per the original number of those in the pool.
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index hex value of MD5 div selected
1 4C4C5D58AD807B5F7F2AF204388DD535 25 -> 1 <-
2 8D48578ABB4CEBD0D2373D7BFA114B03 24 -> 5 <-
3 40A00B09ADC221A1BC94A630586EAACB 23 -> 3 <-
4 7A4E4438A12D0910DD476C4D49320AE8 22 -> 22 <-
5 1043E7D40B3AC046DA0B0632A5D77F94 21 -> 23 <-
6 E1D86C731699BB622DF9D1CE6151CED9 20 -> 13 <-
7 AF58AE51C1C71F5A3F7188DDB6C06C4B 19 -> 6 <-
8 B8C194EDAF398382F12AF1C9FC422EFD 18 -> 17 <-
9 1171E43E16401EDDB49E8949054A6074 17 -> 24 <-
10 88EDB93DE271B27E128D15A52E187064 16 -> 9 <-
11 5DB41AEA8D9764A060C028C9E4092E3A 15 -> 11 <-
12 EA5CCD27C45DF460DBCC6503ECF02D91 14 -> 8 <-
13 F01CCAD753E7ECE2F1FC0BB8E31B32B8 13 -> 12 <-
14 96ED6645A39FDB677074393DB3F3B65B 12 -> 25 <-
15 F52D14524C05F3C9D5E37287EA57BF89 11 -> 15 <-
16 5D91C0594E5A14CE4DD0B0E161330F8E 10 -> 14 <-
17 E2F54F8469968D9F7587030846F667A4 9 -> 4 <-
18 3BCFF32BCFB28F7084FA1D6662C8FDF2 8 -> 10 <-
19 4ECAB2922E136FA17792308C6928AF4F 7 -> 19 <-
20 3A69AEBA4536019CE648DEC72A18202E 6 -> 16 <-
21 73BFBF62ADD6EDE4D49132434A4CB157 5 -> 2 <-
22 08BF9083A8CD26BA51CB69524146648E 4 -> 20 <-
23 7D11231987541D6378827AB916655EC0 3 -> 7 <-
24 3598FF9C59D14E6FFFC0CC3448F99BB3 2 -> 21 <-
25 3D31BDC8D0C4DC0A4B4A07B8F5A17EB2 1 -> 18 <-
Resulting first ten selected, in order selected:
1. John (1) 6. Pandora (13)
2. Sleepy (5) 7. Grouchy (6)
3. Bashful (3) 8. Lee (17)
4. Sloth (22) 9. Anger (24)
5. Envy (23) 10. Handsome (9)
Should one of the above turn out to be ineligible or decline to
serve, the next would be Pollyanna, number 11.
7. Security Considerations
Careful choice of should be made of randomness inputs so that there
is no reasonable suspicion that they are under the control of the
administrator. Guidelines given above to use a small number of
inputs with a substantial amount of entropy from the last should be
followed. And equal care needs to be given that the algorithm
selected is faithfully executed with the designated inputs values.
Publication of the results and a week or so window for the community
of interest to duplicate the calculations should give a reasonable
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assurance against implementation tampering.
8. Reference Code
This code makes use of the MD5 reference code from [RFC 1321] ("RSA
Data Security, Inc. MD5 Message-Digest Algorithm"). The portion of
the code dealing with multiple floating point numbers was written by
Matt Crawford.
/****************************************************************
*
* Reference code for
* "Publicly Verifiable NomCom Random Selection"
* Donald E. Eastlake 3rd
* November 2001
*
****************************************************************/
#include <limits.h>
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include "global.h"
#include "MD5.h"
/* local prototypes */
int longremainder ( unsigned char divisor,
unsigned char dividend[16] );
int getinteger ( char *string );
double NPentropy ( int N, int P );
/* limited to up to 16 inputs of up to sixteen integers each */
/****************************************************************/
main ()
{
int i, j, k, k2, err, keysize, pool, selection;
unsigned char unch, uc16[16], remaining, *selected;
long int temp, array[16];
MD5_CTX ctx;
char buffer[257], key [800], sarray[16][256];
pool = getinteger ( "Type size of pool:\n" );
if ( pool > 255 )
{
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printf ( "Pool too big.\n" );
exit ( 1 );
}
selected = (unsigned char *) malloc ( pool );
if ( !selected )
{
printf ( "Out of memory.\n" );
exit ( 1 );
}
selection = getinteger ( "Type number of items to be selected:\n" );
if ( selection > pool )
{
printf ( "Pool too small.\n" );
exit ( 1 );
}
if ( selection == pool )
printf ( "All of the pool is selected.\n" );
else
{
err = printf ( "Approximately %.1f bits of entropy needed.\n",
NPentropy ( selection, pool ) + 0.1 );
if ( err <= 0 ) exit ( 1 );
}
for ( i = 0, keysize = 0; i < 16; ++i )
{
if ( keysize > 500 )
{
printf ( "Too much input.\n" );
exit ( 1 );
}
/* get the "random" inputs. echo back to user so the user may
be able to tell if truncation or other glitches occur. */
err = printf (
"\nType #%d randomness or 'end' followed by new line.\n"
"Up to 16 integers or the word 'float' followed by up\n"
"to 16 x.y format reals.\n", i+1 );
if ( err <= 0 ) exit ( 1 );
gets ( buffer );
j = sscanf ( buffer,
"%ld%ld%ld%ld%ld%ld%ld%ld%ld%ld%ld%ld%ld%ld%ld%ld",
&array[0], &array[1], &array[2], &array[3],
&array[4], &array[5], &array[6], &array[7],
&array[8], &array[9], &array[10], &array[11],
&array[12], &array[13], &array[14], &array[15] );
if ( j == EOF )
exit ( j );
if ( !j )
if ( buffer[0] == 'e' )
break;
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else
{ /* floating point code by Matt Crawford */
j = sscanf ( buffer,
"float %ld.%[0-9]%ld.%[0-9]%ld.%[0-9]%ld.%[0-9]"
"%ld.%[0-9]%ld.%[0-9]%ld.%[0-9]%ld.%[0-9]"
"%ld.%[0-9]%ld.%[0-9]%ld.%[0-9]%ld.%[0-9]"
"%ld.%[0-9]%ld.%[0-9]%ld.%[0-9]%ld.%[0-9]",
&array[0], sarray[0], &array[1], sarray[1],
&array[2], sarray[2], &array[3], sarray[3],
&array[4], sarray[4], &array[5], sarray[5],
&array[6], sarray[6], &array[7], sarray[7],
&array[8], sarray[8], &array[9], sarray[9],
&array[10], sarray[10], &array[11], sarray[11],
&array[12], sarray[12], &array[13], sarray[13],
&array[14], sarray[14], &array[15], sarray[15] );
if ( j == 0 || j & 1 )
printf ( "Bad format." );
else {
for ( k = 0, j /= 2; k < j; k++ )
{
/* strip trailing zeros */
for ( k2=strlen(sarray[k]); sarray[k][--k2]=='0';)
sarray[k][k2] = '\0';
err = printf ( "%ld.%s\n", array[k], sarray[k] );
if ( err <= 0 ) exit ( 1 );
keysize += sprintf ( &key[keysize], "%ld.%s",
array[k], sarray[k] );
}
keysize += sprintf ( &key[keysize], "/" );
}
}
else
{ /* sort values, not a very efficient algorithm */
for ( k2 = 0; k2 < j - 1; ++k2 )
for ( k = 0; k < j - 1; ++k )
if ( array[k] > array[k+1] )
{
temp = array[k];
array[k] = array[k+1];
array[k+1] = temp;
}
for ( k = 0; k < j; ++k )
{ /* print for user check */
err = printf ( "%ld ", array[k] );
if ( err <= 0 ) exit ( 1 );
keysize += sprintf ( &key[keysize], "%ld.", array[k] );
}
keysize += sprintf ( &key[keysize], "/" );
}
} /* end for i */
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/* have obtained all the input, now produce the output */
err = printf ( "Key is:\n %s\n", key );
if ( err <= 0 ) exit ( 1 );
for ( i = 0; i < pool; ++i )
selected [i] = i + 1;
printf ( "index hex value of MD5 div selected\n" );
for ( unch = 0, remaining = pool;
unch < pool;
++unch, --remaining )
{
MD5Init ( &ctx );
MD5Update ( &ctx, &unch, 1 );
MD5Update ( &ctx, (unsigned char *)key, keysize );
MD5Update ( &ctx, &unch, 1 );
MD5Final ( uc16, &ctx );
k = longremainder ( remaining, uc16 );
/* printf ( "Remaining = %d, remainder = %d.\n", remaining, k ); */
for ( j = 0; j < pool; ++j )
if ( selected[j] )
if ( --k < 0 )
{
printf ( "%2d "
"%02X%02X%02X%02X%02X%02X%02X%02X%02X%02X%02X%02X%02X%02X%02X%02X "
"%2d -> %2d <-\n",
unch+1, uc16[0],uc16[1],uc16[2],uc16[3],uc16[4],uc16[5],uc16[6],
uc16[7],uc16[8],uc16[9],uc16[10],uc16[11],uc16[12],uc16[13],uc16[14],
uc16[15], remaining, selected[j] );
selected[j] = 0;
break;
}
}
printf ( "\nDone, type any character to exit.\n" );
getchar ();
return 0;
}
/* prompt for a positive non-zero integer input */
/****************************************************************/
int getinteger ( char *string )
{
int i, j;
char tin[257];
while ( 1 )
{
printf ( string );
printf ( "(or 'exit' to exit) " );
gets ( tin );
j = sscanf ( tin, "%d", &i );
if ( ( j == EOF )
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INTERNET-DRAFT Verifiable Random Selection November 2001
|| ( !j && ( ( tin[0] == 'e' ) || ( tin[0] == 'E' ) ) )
)
exit ( j );
if ( ( j == 1 ) &&
( i > 0 ) )
return i;
} /* end while */
}
/* get remainder of dividing a 16 byte unsigned int
by a small positive number */
/****************************************************************/
int longremainder ( unsigned char divisor,
unsigned char dividend[16] )
{
int i;
long int kruft;
if ( !divisor )
return -1;
for ( i = 0, kruft = 0; i < 16; ++i )
{
kruft = ( kruft << 8 ) + dividend[i];
kruft %= divisor;
}
return kruft;
} /* end longremainder */
/* calculate how many bits of entropy it takes to select N from P */
/****************************************************************/
/* P!
log ( ----------------- )
2 N! * ( P - N )!
*/
double NPentropy ( int N, int P )
{
int i;
double result = 0.0;
if ( ( N < 1 ) /* not selecting anything? */
|| ( N >= P ) /* selecting all of pool or more? */
)
return 0.0; /* degenerate case */
for ( i = P; i > ( P - N ); --i )
result += log ( i );
for ( i = N; i > 1; --i )
result -= log ( i );
/* divide by [ log (base e) of 2 ] to convert to bits */
result /= 0.69315;
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return result;
} /* end NPentropy */
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Appendix A: History of NomCom Member Selection
For reference purposes, here is a list of the IETF Nominations
Committee member selection techniques and chairs so far:
YEAR CHAIR SELECTION METHOD
1993/1994 Jeff Case Clergy
1994/1995 Fred Baker Clergy
1995/1996 Guy Almes Clergy
1996/1997 Geoff Huston Spouse
1997/1998 Mike St.Johns Algorithm
1998/1999 Donald Eastlake 3rd This Algorithm
1999/2000 Avri Doria This Algorithm
2000/2001 Bernard Aboba This Algorithm
2001/2002 Theodore Ts'o This Algorithm
Clergy = Names were written on pieces of paper, placed in a
receptacle, and a member of the clergy picked the NomCom members.
Spouse = Same as Clergy except chair's spouse made the selection.
Algorithm = Algorithmic selection based on the same concepts as
documented herein.
This Algorithm = Algorithmic selection using the algorithm and
reference code described herein (but not the fake example sources of
randomness).
Appendix B: Changes from RFC 2777
This document differs from [RFC 2777], the previous version, in two
primary ways as follows:
(1) Section 5, on problems actually encountered with recommendations
on how to handle them, has been added.
(2) The selection algorithm and code have been recast from selection
N entries from the pool to producing a total ordering of the
pool. It is then easy to pick N by just taking the first N. This
handles cases where some pool entries turn out to be ineligible,
etc.
Other minor changes and updates were made.
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References
[RFC 1321] - "The MD5 Message-Digest Algorithm", R. Rivest. April
1992.
[RFC 1750] - "Randomness Recommendations for Security", D. Eastlake,
3rd, S. Crocker & J. Schiller. December 1994.
[RFC 2727] - "IAB and IESG Selection, Confirmation, and Recall
Process: Operation of the Nominating and Recall Committees", J.
Galvin, February 2000.
[RFC 2777] - "Publicly Verifiable Nomcom Random Selection", D.
Eastlake, February 2000.
[RFC 3174] - "US Secure Hash Algorithm 1 (SHA1)", D. Eastlake, 3rd,
P. Jones, September 2001.
Author's Address
Donald E. Eastlake, 3rd
Motorola
155 Beaver Street
Milford, MA 01757 USA
tel: +1-508-261-5434(w)
+1-508-634-2066(h)
fax: +1-508-261-4447(w)
email: Donald.Eastlake@motorola.com
File name and Expiration
This file is draft-eastlake-rfc2777bis-selection-01.txt.
It expires May 2002.
D. Eastlake 3rd [Page 19]